Computer networks, both public and private, have grown rapidly in recent years. A good example of a rapidly growing public network is the Internet. The Internet is made of a huge variety of hosts, links and networks. The diversity of large networks like the Internet presents challenges to servers operating in such networks. For example, a web server whose goal is to provide the best possible service to clients must contend with performance problems that vary in their nature and that vary over time. For example performance problems result from network delays, poor throughput and high incidents of packet losses. These problems are measurable, but it is difficult to pinpoint the portion of a large network that is responsible for the problems observed at either the client or the server.
Many techniques currently exist for measuring network performance. Some of the techniques are active, in that they involve injecting data traffic into the network in the form of pings, traceroutes, and TCP connections. Other techniques are passive in that they involve analyzing existing traffic by using server logs, packet sniffers, and the like. Most of these techniques measure end-to-end performance. That is, they measure the aggregate performance of the network from a server to a client, including all of the intermediate, individual network links, and make no effort made to distinguish among the performance of individual links. The few techniques that attempt to infer the performance of portions of the network (e.g., links between nodes) typically employ active probing (i.e., inject additional traffic into the network), which would place an additional burden on the network.